کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4944746 | 1438004 | 2017 | 33 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
From coarse- to fine-grained implementation of edge-directed interpolation using a GPU
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
The new edge-directed interpolation (NEDI) algorithm is non-iterative and orientation-adaptive. It achieves better edge performance in enhancing remote sensing images and natural images than conventional bi-linear and bi-cubic methods. It is also the theoretical foundation of many other complex regression and auto-regression interpolation methods. Although NEDI has impressive performance, its computation complexity is an obstacle to large-scale expansion. Parallel acceleration of NEDI provides strong versatility and extensibility. In this paper, we propose a fine-grained implementation for NEDI using GPU . In the fine-grained approach, we assign calculations of one unknown pixel to 2âÃâ2, 2âÃâ4, and 4âÃâ4 threads. Using NVIDIA TESLA K40C GPU for a case of asynchronous I/O transfer, our GPU optimization efforts using fine-grained NEDI can achieve a speedup of 99.09-fold when considering the I/O transfer time, compared with the original single-threaded C CPU code with the -O2 compiling optimization on Intel core⢠i7-920. To demonstrate the effectiveness of our fine-grained scheme, we also compare the fine- and coarse-grained schemes by interpolating a 720p video to 1440p. Adopting the fine-grained scheme, we can achieve real-time display. The fine-grained parallel mode can be expanded to other algorithms based on regression and auto-regression schemes.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volumes 385â386, April 2017, Pages 457-474
Journal: Information Sciences - Volumes 385â386, April 2017, Pages 457-474
نویسندگان
Jiaji Wu, Wenze Li, Gwanggil Jeon,